Enhancing Cybersecurity Through Mobile Number Credibility Assessment
In the face of escalating cyber threats impacting national security and economic stability, this paper presents the Mobile No. Credibility Quotient (MNCQ), an innovative solution for enhancing mobile number authentication and strengthening global cybersecurity. The MNCQ utilizes a dynamic metric system to evaluate mobile number credibility, countering cybercriminals who exploit the process of acquiring mobile numbers which are quintessential to hiring infrastructure being used for purporting cybercrime. It employs extensive datasets, such as social security and government records, to validate mobile connections. The MNCQ's adaptability transcends borders, offering a scalable model for various regions and data pools. It encourages academia-industry partnerships for research, driving forward its integration into tech infrastructures via the MNCQ API for real-time assessments, thus bolstering cyber defenses. Furthermore, MNCQ facilitates international collaboration against cybercrime, underscoring the need for shared cybersecurity frameworks in today's interconnected digital landscape. Nations would be able to calibrate the MNCQ system as per their own cybersecurity needs and nation specific legal requirements, ensuring the efficacy of the MNCQ within their own borders while addressing local cyber-crimes.In the context of escalating cyber threats, the MNCQ presents an innovative solution for mobile number authentication, crucial for cyber defense. It utilizes a dynamic metric to evaluate the credibility of mobile numbers, a common vulnerability exploited by cybercriminals. By leveraging diverse data points, MNCQ strengthens cybersecurity, supports proactive threat mitigation, and fosters global collaboration against cybercrime.
Authors
- Vineet Kumar (ORCID: https://orcid.org/0000-0002-2602-9181)
- Shailesh Tiwary
- Rohit Malpani
Institutions
- Indian Health Service (US)
- Indian Army (IN)
Publication Details
- Published
- 2024-10-17
- DOI
- https://doi.org/10.1109/icbds61829.2024.10837419
- Primary Topic
- Spam and Phishing Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00